Summary

Model v0.2.3 was created using wind, lag_sst, int_chl, sss for cfin. The models were averaged into climatologies with one climatology per month. Evaluations were compiled from the climatological averages and plotted. Finally, the study area was divided up into three regions, the Mid-Atlantic Bight (MAB), George’s Bank (GBK), and the Gulf of Maine (GOM). Actual versus predicted abundance values were plotted for each region. The mgvc GAMs and the gbm BRTs were run using the CPR dataset(s). The Biomod2 models were run using the ECOMON dataset(s). If the model is an anomaly, all datasets are used.

Biomod: right whale feeding threshold models

Climatologies

Biomod Ensemble Climatology

The ensemble models were created using the biomod2 package. The ensembles consist of BRTs, GAMs, and random forests (RFs). The ensembles were used to model the right whale feeding threshold, with any abundance greater than 10^{4} cfin per \(m^2\) counted as a presence and anything below that threshold counted as an absence.

Figure 1. Monthly climatological ensemble projections of GAMs, BRTs, and random forests (RFs). The climatology was created by averaging together the projections from 2000 to 2017.

GAM Climatology

The GAM models created with biomod2 were used to model the right whale feeding threshold, with any abundance greater than 10^{4} cfin per \(m^2\) counted as a presence and anything below that threshold counted as an absence.

Figure 2. Monthly climatological GAM projections produced using Biomod2. The climatology was created by averaging together the projections from 2000 to 2017.

BRT Climatology

The BRT models created with biomod2 were used to model the right whale feeding threshold, with any abundance greater than 10^{4} cfin per \(m^2\) counted as a presence and anything below that threshold counted as an absence.

Figure 3. Monthly climatological BRT projections produced using Biomod2. The climatology was created by averaging together the projections from 2000 to 2017.

RF Climatology

The RF models created with biomod2 were used to model the right whale feeding threshold, with any abundance greater than 10^{4} cfin per \(m^2\) counted as a presence and anything below that threshold counted as an absence.

Figure 4. Monthly climatological RF projections produced using Biomod2. The climatology was created by averaging together the projections from 2000 to 2017.

Monthly ensemble projections

Monthly ensemble Biomod2 projections are displayed below for the months of May, June, July, August, and September.

April

Figure 5. Ensemble projections for the month of April over 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017.

May

Figure 6. Ensemble projections for the month of May over 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017.

June

Figure 7. Ensemble projections for the month of June over 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017.

August

Figure 8. Ensemble projections for the month of August over 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017.

September

Figure 9. Ensemble projections for the month of September over 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017.

Evaluations

Evaluation metrics differed based on the metrics available in each modeling package and compatible with each model object. For the mgcv GAMs, Aikaike’s Information Criterion (AIC), the root mean squared error (RMSE), and the R squared (RSQ) value when comparing the actual and predicted abundances were computed. For the BRTs produced using the gbm package, RMSE and RSQ were computed. For the biomod2 ensembles and GAMs, the area under the receiver operator characteristic curve (AUC) and the true skill statistic (TSS) were computed.

Ensemble evaluations

Figure 10. Biomod ensemble evaluations on a monthly time scale using a.) AUC and b.) TSS

GAM evaluations

Figure 11. Biomod GAM evaluations on a monthly time scale using a.) AUC and b.) TSS

BRT evaluations

Figure 12. Biomod BRT evaluations on a monthly time scale using a.) AUC and b.) TSS

RF evaluations

Figure 13. Biomod RF evaluations on a monthly time scale using a.) AUC and b.) TSS

Variable contribution

GAM variable contribution

Figure 14. Biomod GAM variable contributions on a monthly time scale.

BRT variable contribution

Figure 15. Biomod BRT variable contributions on a monthly time scale.

RF variable contribution

Figure 16. Biomod RF variable contributions on a monthly time scale.

Actual abundance vs. predicted probability of suitability

Biomod ensemble

For the biomod ensemble models, the logged actual abundance of cfin was plotted against the predicted probability of suitability. Above the threshold of 10^{4}, the probability of suitability tends to increase. Below the threshold, the probability of suitability tends to be zero.

Figure 17. Actual logged abundance versus predicted probability of suitability for cfin for all 12 months.

Ensemble region plots

GAM region plots

BRT region plots

RF region plots

MGCV GAMs

Climatology

The generalized additive models (GAMs) were run using the mgcv package and were used to model cfin abundances.

Figure 18. Monthly climatological GAM projections. The climatology was created by averaging together the projections from 2000 to 2017.

Evaluations

Figure 19. Model evaluations on a monthly time scale using a.) AIC, b.) RMSE, and c.) R2.

Regions

The study area was divided into three regions, the MAB, GBK, and GOM. For each region, a climatological average (one point per month), monthly average time series, and annual average time series were computed and the actual versus predicted abundance values were plotted.

Climatological average

Figure 20. Climatological abundance values averaged over three regions, a.) the Mid Atlantic Bight, b.) George’s Bank, and c.) the Gulf of Maine. The predicted values come from the projections.

Monthly average time series

Figure 21. Abundance values averaged monthly over three regions, a.) the Mid Atlantic Bight, b.) George’s Bank, and c.) the Gulf of Maine. The predicted values come from the projections.

Annual average time series

Figure 22. Abundance values averaged annually over three regions, a.) the Mid Atlantic Bight, b.) George’s Bank, and c.) the Gulf of Maine. The predicted values come from the projections.

Actual vs predicted values

Actual abundance values were plotted against predicted abundance values.

Figure 23. Actual logged abundance versus logged predicted abundance for cfin for all 12 months.

GBM BRTs

Climatology

The boosted regression tree (BRT) models were run using the gbm package and used to model cfin abundances.

Figure 24. Monthly climatological BRT projections. The climatology was created by averaging together the projections from 2000 to 2017.

Evaluations

Figure 25. Model evaluations on a monthly time scale using a.) RMSE and b.) R2.

Regions

The study area was divided into three regions, the MAB, GBK, and GOM. For each region, a climatological average (one point per month), monthly average time series, and annual average time series were computed and the actual versus predicted abundance values were plotted.

Climatological average

Figure 26. Climatological abundance values averaged over three regions, a.) the Mid Atlantic Bight, b.) George’s Bank, and c.) the Gulf of Maine. The predicted values come from the projections.

Monthly average time series

Figure 27. Abundance values averaged monthly over three regions, a.) the Mid Atlantic Bight, b.) George’s Bank, and c.) the Gulf of Maine. The predicted values come from the projections.

Annual average time series

Figure 28. Abundance values averaged annually over three regions, a.) the Mid Atlantic Bight, b.) George’s Bank, and c.) the Gulf of Maine. The predicted values come from the projections.

Actual vs. predicted values

Actual abundance values were plotted against predicted abundance values.

Figure 29. Actual logged abundance versus logged predicted abundance for cfin for all 12 months.